ArticleJournal of clinical pharmacology2020
Application of Physiologically Based Pharmacokinetic Modeling to Predict Drug Exposure and Support Dosing Recommendations for Potential Drug-Drug Interactions or in Special Populations: An Example Using Tofacitinib.
Article in Journal of clinical pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on disease-drug-drug interactions with immunomodulating drugs: A critical appraisal of risk assessment and drug labelling.British journal of clinical pharmacology · 2022Pooled it
- Exploration of IVIVC Deconvolution Methods in a PBPK Platform: Case Example with Tofacitinib.The AAPS journal · 2026Trial
- Physiologically Based Pharmacokinetic Simulation of Tofacitinib in Humans Using Extrapolation from Single-Species Renal Failure Model.Pharmaceutics · 2025Article
- Virtual Bioequivalence Assessment of Tofacitinib Once Daily Modified Release Dosage Form in Pediatric Subjects.The AAPS journal · 2025Article
- Physiologically Based Pharmacokinetic Modeling of Tofacitinib: Predicting Drug Exposure and Optimizing Dosage in Special Populations and Drug-Drug Interaction Scenarios.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective.Clinical pharmacology and therapeutics · 2025Review
- The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases.Pharmaceutics · 2024Review
- Conventional vs Mechanistic IVIVC: A Comparative Study in Establishing Dissolution Safe Space for Extended Release Formulations.AAPS PharmSciTech · 2024Article
- Safety of Janus kinase inhibitors compared to biological DMARDs in patients with rheumatoid arthritis and renal impairment: the ANSWER cohort study.Clinical and experimental medicine · 2024Observational
- Physiologically-Based Pharmacokinetic Modelling to Investigate Baricitinib and Tofacitinib Dosing Recommendations for COVID-19 in Geriatrics.Clinical pharmacology and therapeutics · 2022Article
- Ulcerative Colitis in Adulthood and in Older Patients: Same Disease, Same Outcome, Same Risks?Drugs & aging · 2022Review
- Efficacy and Safety of Ertugliflozin in Type 2 Diabetes: A Systematic Review and Meta-Analysis.Frontiers in pharmacology · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis, psoriatic arthritis, and ulcerative colitis. It is eliminated via multiple pathways including oxidative metabolism (∼70%) and renal excretion (29%). This study aimed to predict the impact of drug-drug interactions and renal or hepatic impairment on tofacitinib pharmacokinetics using a physiologically based pharmacokinetic (PBPK) model. The model was developed using Simcyp based on the physicochemical properties and in vitro and in vivo pharmacokinetics data for tofacitinib. The model was verified by comparing the predicted pharmacokinetic profiles with those observed in available clinical studies after single or multiple doses of tofacitinib, as well as with tofacitinib as a victim of drug-drug interactions (because of inhibition of cytochrome P450 [CYP450] 3A4, CYP450 2C19, or CYP450 induction). In general, good agreement was observed between Simcyp predictions and clinical data. The results from this study provide confidence in using the PBPK modeling and simulation approach to predict the pharmacokinetics of tofacitinib under intrinsic (eg, renal or hepatic impairment) or extrinsic (eg, inhibition of CYP450 enzymes and/or renal transporters) conditions. This approach may also be useful in predicting pharmacokinetics under untested or complex situations (eg, when a combination of intrinsic and extrinsic factors may impact pharmacokinetics) when conducting clinical studies may be difficult, in response to health authority questions regarding dosing in special populations, or for labeling discussions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.